In state-of-art video coding schemes, block-based motion compensated prediction (MCP) is used to exploit temporal redundancy. For inter-view coding in a multi-view video coding (MVC) scenario, a block matching procedure can also be applied to perform disparity compensated prediction (DCP), thus exploiting inter-view redundancy. These techniques achieve high coding efficiency for translational displacement. However, there exist mismatches in the video content that are beyond translational displacement such as, for example, focus changes, motion blur in monoscopic video, and illumination and focus mismatches across different views in multi-video video coding.
In the context of video coding, adaptive filtering approaches have previously been proposed to improve coding efficiency. For example, subpel motion compensation has been proposed. Such proposals involve an adaptive interpolation filtering (AIF) method, which introduces two-dimensional (2D) non-separable filters as compared to the interpolation filters of the International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) Moving Picture Experts Group-4 (MPEG-4) Part 10 Advanced Video Coding (AVC) standard/International Telecommunication Union, Telecommunication Sector (ITU-T) H.264 Recommendation (hereinafter the “MPEG-4 AVC Standard”). In the AIF method, for encoding B-frames, one set of interpolation filters are estimated for different subpel positions, and then applied to references in both List 0 and List 1. Hence, the AIF method is deficient in that it does not separately consider the possible different types of mismatches from List 0 and from List 1. That is, estimating and/or applying more than one set of filters to different lists is not enabled in the AIF method.